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Ismael Flores

dblp:181/4272 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot navigation and mapping · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › state estimation
observability analysis
0.212016
Observability analysis and optimal sensor placement in stereo radar odometry · ICRA 2016
Robotics › Robot navigation and mapping › localization
odometry
0.212016
Observability analysis and optimal sensor placement in stereo radar odometry · ICRA 2016
Robotics › Robot navigation and mapping › localization › odometry
radar odometry
0.212016
Observability analysis and optimal sensor placement in stereo radar odometry · ICRA 2016
Robotics › Robot navigation and mapping › sensor planning
sensor placement
0.212016
Observability analysis and optimal sensor placement in stereo radar odometry · ICRA 2016

Methods — techniques the papers use, named apart from their topics

doppler error modeling · 0.2
YearPublicationVenuePosition
2016 Observability analysis and optimal sensor placement in stereo radar odometry
abstract
Localization is the key perceptual process closing the loop of autonomous navigation, allowing self-driving vehicles to operate in a deliberate way. To ensure robust localization, autonomous vehicles have to implement redundant estimation processes, ideally independent in terms of the underlying physics behind sensing principles. This paper presents a stereo radar odometry system, which can be used as such a redundant system, complementary to other odometry estimation processes, providing robustness for long-term operability. The presented work is novel with respect to previously published methods in that it contains: (i) a detailed formulation of the Doppler error and its associated uncertainty; (ii) an observability analysis that gives the minimal conditions to infer a 2D twist from radar readings; and (iii) a numerical analysis for optimal vehicle sensor placement. Experimental results are also detailed that validate the theoretical insights.
Andreu Corominas Murtra, Joan Vallvé, Joan Solà, Ismael Flores, Juan Andrade-Cetto
ICRA4